135 citations · 232 across the 12 of their papers we have counts for
5 papers · 1 filter
Cross-Task Inconsistency Based Active Learning (CTIAL) for Emotion Recognition
Yifan Xu, Xue Jiang, Dongrui Wu
Emotion recognition is a critical component of affective computing. Training accurate machine learning models for emotion recognition typically requires a large amount of labeled d…
Self-supervised Contrastive Learning for EEG-based Sleep Staging
Xue Jiang, Jianhui Zhao, Bo Du +1
EEG signals are usually simple to obtain but expensive to label. Although supervised learning has been widely used in the field of EEG signal analysis, its generalization performan…
MRNet: a Multi-scale Residual Network for EEG-based Sleep Staging
Xue Jiang
Sleep staging based on electroencephalogram (EEG) plays an important role in the clinical diagnosis and treatment of sleep disorders. In order to emancipate human experts from heav…
Pool-Based Unsupervised Active Learning for Regression Using Iterative Representativeness-Diversity Maximization (iRDM)
Ziang Liu, Xue Jiang, Hanbin Luo +3
Active learning (AL) selects the most beneficial unlabeled samples to label, and hence a better machine learning model can be trained from the same number of labeled samples. Most…
Active Learning for Black-Box Adversarial Attacks in EEG-Based Brain-Computer Interfaces
Xue Jiang, Xiao Zhang, Dongrui Wu
Deep learning has made significant breakthroughs in many fields, including electroencephalogram (EEG) based brain-computer interfaces (BCIs). However, deep learning models are vuln…